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Drawbacks to resolution theorem:
Thus the underlining here identifies some drawbacks to resolution theorem proving:
Just cannot to check at the same time where a conjecture is true or false, but it can't work in higher order logics. So if there are related techniques which address these problems, than to varying degrees of success.
So notwithstanding these drawbacks, there resolution theorem proving is a complete method: but if your theorem does follow from the axioms of a domain so such resolution can prove it. However, it only uses one rule of deduction the resolution but the multitude we saw in the last lecture. Thus it is comparatively simple to understand how resolution theorem provers work. Here for these reasons and the development of the resolution method was a major accomplishment in logic in which with serious implications to "Artificial Intelligence" research.
There resolution works by taking two sentences and resolving them with one ultimately resolving two sentences to produce the False statement. So we can say that the resolution rule is more complicated other than the rules of inference we've seen before we require to cover some preparatory notions before we can understand how it works. Now here in particularly we use to look at conjunctive normal form and unification before we can state the full resolution rule at the heart of the resolution method to justified.
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Binary Resolution: However we saw unit resolution for a propositional inference rule in the previous lecture: (A? B, ¬B) /A Thus we can take this a little further to
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